CALL FOR PARTICIPATION

Purpose and Scope

With the amount of textual data increases rapidly, it is important to find not only appropriate, but also more trustworthy answers to user’s natural language questions. Natural language question answering systems have proven to be helpful to users because they can provide succinct answers that do not require users to wade through a large number of documents. In this workshop, we would like to discuss research outcomes of the Korean “Exobrain” project, consisting of natural language processing, information extraction, ontology reasoning and population, question answering technologies.

The theme of this workshop is to discuss recent progress of Natural language question answering technology for providing knowledge services with users. Prospective authors are cordially invited to submit their original contributions covering completed or ongoing work related to the following research areas:

Natural language question analysis

IR-based question answering

Knowledge-based question answering

Natural language processing

Multi-agent communication and problem solving

Autonomous intelligent collaboration framework

Distributed task planning and execution

Ontology-based knowledgebase

Knowledge-based negotiation and verification

Intention recognition and analysis

Information extraction

Paraphrasing and textural entailments

Ontology population and reasoning

PAPER SUBMISSION

Prospective authors are invited to submit their papers, 2~4 pages, in English according to the IEEE two-column format for conference proceedings. The direct link for paper submission is https://easychair.org/conferences/?conf=exobrain2017. All submissions will be peer-reviewed by the Program Committees of the workshop.

IMPORTANT DATES

Paper Submission Due

December 27, 2016January 07, 2017 (Final) (23:59, PST)

Notification of Acceptance

January 05, 2017January 15, 2017

Camera-Ready Papers

January 15, 2017January 18, 2017

Workshop

February 13, 2017

ORGANIZATIONAL COMMITTEE

Organizing Co-Chairs

Sang-Kyu Park, ETRI, Korea

Ho-Jin Choi, KAIST, Korea

Program Committee

Chang-Eun Lee, ETRI, Korea

Cheol-Young Ok, Ulsan University, Korea

Gahgene Gweon, Seoul National University, Korea

Ho-Jin Choi, KAIST, Korea

Hyunki Kim, ETRI, Korea

Il Hong Suh, Hanyang University, Korea

Jae Sung Lee, Chungbuk National University, Korea

Jongho Nang, Sogang University, Korea

Key-Sun Choi, KAIST, Korea

Kyung-IL Lee, Saltlux, Korea

Se-Young Park, Kyungbook University, Korea

Sung-Hyon Myaeng, KAIST, Korea

Young-guk Ha, Konkuk University, Korea

Young-Tack Park, Soongsil University, Korea

KEYNOTE SPEECH

Korean Semantic Resources & Korean Semantic Processing Systems

Speaker

Cheol-Young Ock

Professor, School of IT Convergence, University of Ulsan, Korea

Abstract

For semantic processing such as sentence understanding and QA, many sematic resources are needed. One of most important semantic resources is a semantic network. Prof. Ock has been constructing a Korean WordNet, namely Ulsan Word Map (UWordMap) since 2002. The Ulsan Word Map has semantic hierarchy(hypernym and hyponym) like WordNet, but it has another important information, subcategorization of argument of predicate. In this speech Prof. Ock will introduce a structure of the UWordMap and how to use for word sense disambiguation of Korean and for understanding a Query in Exo Brain SW.

Word representation, an important area in natural language processing(NLP) used machine learning, is a method that represents a word not by text but by distinguishable symbol. Existing word embedding employed a large number of corpora to ensure that words that were position near by in text. However, corpus-base word embedding need a lot of corpora because the frequency of word occurrence and increase the number of words. Another word embedding(Sense Vector) is done using dictionary definitions and semantic relationship information(hypernyms and antonyms). Then similar sense’s words have similar vector. Furthermore, it was possible to distinguish vectors of antonym words. In this speech Prof. Ock will introduce the Sense Vector and its applications of sematic operations.

Bio

Cheol-Young Ock is a professor of the school of IT convergence, University of Ulsan, Ulsan, Rep. of Korea. He received his BS (1982), MS (1984), and PhD (1993) degrees in computer engineering from the National University of Seoul, Seoul, Rep. of Korea. He has been a visiting professor at the Russia Tomsk Institute (1994) and Glasgow University (1996). He has been the chairman of the sigHCLT (2007~2008) in the KIISE, Rep. of Korea. He has been a visiting researcher at the National Institute of Korean Language (2008). He received an honorary doctorate from the department of Information and Computer Science, National University of Mongolia, Ulaanbaatar, Mongolia (2007). He received a government medal as a meritorious engineer of Korean language development (2016). He has been constructing a Korean WordNet, namely Ulsan Word Map (UWordMap) since 2002. His research interests include natural language processing (WSD), machine learning, and text mining.